ESSENTIALS OF MARKETING RESEARCH
Hair/Wolfinbarger/Ortinau/Bush
Explain the role of sampling in the
research process
Distinguish between probability and
nonprobability sampling
Understand the factors to consider
when determining sample size
Understand the steps in developing a
sampling plan
Sampling is the process
of selecting a small number of elements
from a larger defined target group
of elements such that
the information gathered
from the small group will allow judgments
to be made about the larger groups
Population
Element
Defined target
population
Sampling unit
Sampling frame
Sampling error is any type of bias
that is attributable to mistakes
in either drawing a sample or
determining the sample size
1. Define the Population of Interest
2. Identify a Sampling Frame (if possible)
3. Select a Sampling Method
4. Determine Sample Size
5. Execute the Sampling Plan
Population of interest is entirely dependent
on Management Problem, Research Problems,
and Research Design.
Some Bases for Defining Population:
◦ Geographic Area
◦ Demographics
◦ Usage/Lifestyle
◦ Awareness
A list of population elements (people,
companies, houses, cities, etc.) from which
units to be sampled can be selected.
Difficult to get an accurate list.
Sample frame error occurs when certain
elements of the population are accidentally
omitted or not included on the list.
See Survey Sampling International for some
good examples
http://www.surveysampling.com/
Probability Nonprobability
sampling sampling
Probability Nonprobability
Simple random Convenience
sampling sampling
Systematic random Judgment sampling
sampling Quota sampling
Stratified random Snowball sampling
sampling
Cluster sampling
Simple random sampling is a method of
probability sampling in which
every unit has an equal nonzero
chance of being selected
Systematic random sampling is a
method of
probability sampling
in which the defined
target population is ordered
and the sample is selected
according to position using a skip interval
1: Obtain a list of units that contains an
acceptable frame of the target population
2: Determine the number of units in the list
and the desired sample size
3: Compute the skip interval
4: Determine a random start point
5: Beginning at the start point, select the
units by choosing each unit that
corresponds to the skip interval
Stratified random sampling is a
method of
probability sampling
in which the population is divided
into different subgroups and samples
are selected from each
1: Divide the target population into
homogeneous subgroups or strata
2: Draw random samples fro each stratum
3: Combine the samples from each stratum
into a single sample of the target
population
Convenience sampling relies
upon convenience and access
Judgment sampling relies upon belief
that participants fit characteristics
Quota sampling emphasizes representation
of specific characteristics
Snowball sampling relies upon respondent
referrals of others with like characteristics
Research objectives Degree of accuracy
Resources Time frame
Knowledge of
target population Research scope
Statistical analysis needs
How many completed questionnaires do we
need to have a representative sample?
Generally the larger the better, but that takes
more time and money.
Answer depends on:
◦ How different or dispersed the population is.
◦ Desired level of confidence.
◦ Desired degree of accuracy.
Common Methods:
◦ Budget/time available
◦ Executive decision
◦ Statistical methods
◦ Historical data/guidelines
See Table
Variability of the population characteristic
under investigation
Level of confidence desired in the estimate
Degree of precision desired in estimating
the population characteristic
Probability Sampling and
Sample Sizes
When estimating a population mean
n = (Z2B,CL)(σ2/e2)
When estimates of a population proportion
are of concern
n = (Z2B,CL)([P x Q]/e2)
For a simple sample size calculator, click here:
http://www.surveysystem.com/sscalc.htm